Improving Retrievals of Tropospheric NO 2 Randall Martin, Dalhousie and Harvard-Smithsonian Lok Lamsal, Gray O’Byrne, Aaron van Donkelaar, Dalhousie Ed Celarier, Eric Bucsela, Joanna Joiner, NASA Folkert Boersma, Ruud Dirksen, KNMI Chao Luo, Yuhang Wang, Georgia Tech September 14, 2009 Air Quality Working Group Aura Meeting Leiden, Netherlands

Seasonal Differences Between OMI NO 2 Products Direct Validation Has Not Arbitrated Tropospheric NO 2 Column (10 15 molecules cm -2 ) Standard (SP)DOMINO (DP)DP-SP DJF 2005 JJA Δ (10 15 molecules cm -2 ) Lamsal et al., JGR, submitted

Indirect Validation of OMI (A)In-situ surface NO 2 measurements from the SEARCH (photolytic) and EPA/AQS (molybdenum) networks at rural sites in Eastern US Use GEOS-Chem NO 2 profiles to estimate surface-level NO 2 from OMI (Lamsal et al., JGR, 2008) Apply GEOS-Chem to infer top-down emissions from OMI by mass balance (Martin et al., JGR, 2003) (B) Updated bottom-up emission inventories for

Multiple Approaches Yield Similar Results NO x Emissions, SEARCH domain NOx Emissions, US + Canada SEARCH “True” NO 2 ”, Southeast U.S. AQS/EPA “Corrected” NO 2, Eastern U.S. Lamsal et al., JGR, submitted

Stratosphere-troposphere Separation and AMF Together Explain Difference Between DP and SP Air mass factor Strat-trop separation Combined Δ Tropospheric NO 2 Column DP – SP (10 15 molecules cm -2 ) Lamsal et al., JGR, submitted

Produce DP_GC From DP Averaging Kernels and GEOS-Chem NO 2 Profiles NO x Emissions, SEARCH domain NOx Emissions, US + Canada SEARCH “True” NO 2 ”, Southeast U.S. AQS/EPA “Corrected” NO 2, Eastern U.S. Lamsal et al., JGR, submitted

Surface Reflectivity Lambertian Equivalent Reflectivity (LER)

OMI LER (Kleipool et al. 2008) Best Represents Surface LER Use MODIS/Aqua to Eliminate Cloud and Aerosol from OMI Scenes Use NISE Snow Flag to Eliminate Snow Cloud-, Snow-, and Aerosol- Free LER ( ) Global Annual Mean Difference x100 (unitless) Standard Deviation x100 (unitless) TOMS MinLER GOME MinLER OMI MinLER OMI LER (if snow-free) LER Difference of 2%  15-30% Bias in NO 2 (Martin et al., 2002; Boersma et al., 2004) O’Byrne et al., JGR, submitted

Unrealistic Relation in OMI NO 2 versus Cloud & Snow (In situ NO 2 data show variation < 15%) OMI Reported Cloud Fraction ≥ 5cm of snow 0 > snow < 5cm no snow Winter Mean Trop. NO 2 (molec/cm 2 ) Winter OMI NO 2 over Calgary & Edmonton O’Byrne et al., JGR, submitted

Snow-covered Surface LER (unitless) Large Spatial Variation in Snow-Covered Surface LER Current Algorithms Assume Snow Reflectivity = 0.6 Snow Weakly Represented in Previous Climatologies Leads to Ambiguity in Accounting for Snow O’Byrne et al., JGR, submitted Snow-Covered LER Difference (Previous Climatology – Snow-Covered Surface LER) OMI LER

Spatially-Varying Biases in OMI NO 2 over Snow With Cloud Fraction Threshold (f < 0.3) To correct NO 2 retrieval for snow Use snow-covered surface reflectivity Use MODIS-determined cloud-free scenes to correct clouds NO 2 bias for MODIS-determined cloud-free scenes Positive (negative) bias from underestimated (overestimated) surface LER OMI reports clouds when surface LER is underestimated O’Byrne et al., JGR, submitted With All Cloud Fractions

Recommendations Remote Sensing Community: Use two reflectivity databases: one snow-free, one for snow Switch from TOMS or GOME reflectivity databases to OMI Switch from annual mean to monthly mean NO 2 profiles for SP Evaluate Stratosphere-Troposphere Separation Develop instrumentation with finer spatial resolution (more cloud-free scenes reduces dependence on assumed profile ) Following DP, include Averaging Kernels (or Scattering Weights) in trace gas products so the user can remove the effect of the assumed profile Modeling Community: Continue develop representation of vertical profile Ground-based Measurement Needs: span satellite footprint full year research quality (e.g. NO 2 ) vertical profile